一个改进的单抓钩周期性排序模型及其在自动化学处理线中的应用

计算机控制的抓钩广泛用于自动化学处理线的工件的运送。抓钩的排序直接影响系统的生产率，抓钩排序的目标是对运送进行排序以极大化生产率。当某工序处理时间非常长时，该工序成为瓶颈。为了去除该瓶颈，系统可以为该工序设计多个处理槽，这称为“多重处理槽”问题。本文提出一个改进的混合整数规划模型以求解有“多重处理槽”的单抓钩周期性排序问题的最优解。实例表明所提出的方法是有效的。     

电化学整流系统运行及故障处理

介绍了济宁金威煤电集团化工公司6万t／a离子膜烧碱整流系统中,整流变压器、整流柜的特点和联接方式,以及直流测量装置,纯水冷却装置,监控系统的性能和特点,总结了整套系统在连续生产过程中的运行及维修情况,和长期运行过程中整流系统装置,纯水系统,直流传感系统出现的典型故障及处理方法。     

成组单元的作业排序

多品种小批量生产中为提高生产率和经济效益采用成组技术。作业排序是成组技术管理工作中的一个重要问题。本文从多工序成组作业排序的基本方法中着重介绍了一种方法,并结合生产实际应用分析如何进行修正的方法。文中还结合分析对比其他几种方法,指出了本文介绍方法的优点。     

多目标装置技术经济指标综合评价方法原理

论述多目标装置技术经济分析有两类问题:估计装置的生产率与确定每种产品的费用分率。提出复杂能量转化系统的技术经济分析,必须在考虑系统构成的条件下综合研究(?)指标和价格的基础上进行。以“热经济分析法”对KAp—30型和KTK一35型空分装置进行了比较。并分析了θπOy—ABT—6型石油蒸馏装置。指出运用热经济分析法,能客观地估计多目标装置的产品成本。图2表3。     

Yj23接咀机水松纸夹持装置的改进

总结原装置的工作繁琐、生产率低的弱点,简要说明新装置的设计思路及设计原理,并总结新装置的特点。     

基于机器视觉的改进线束导线排序检测系统设计

目的 解决现有工业线束导线排序检测方法中存在的效率低、混色导线检测效果差等问题。方法 基于机器视觉技术设计一种线束导线排序检测装置,并结合图像处理技术和深度学习原理提出一种混色导线排序检测方法。首先根据线束图像中选择的感兴趣区域,分割出线束连接器图像和导线图像,并采用模板匹配和颜色定位方法完成连接器正反面的识别和单色导线的识别定位;然后采集并制作PE混色导线数据集,研究Faster R−CNN、SSD、YOLOv3和YOLOv5m等4种不同目标检测算法对PE混色导线的检测效果。结果 实验结果表明,YOLOv5m检测模型的检测速度和准确率兼顾性最好;改进系统后,检测时间减少了18.55%,平均识别准确率为98.83%。结论 改进后检测系统具有良好的检测效率和可靠性,适用于种类丰富的工业线束导线排序检测。     

继电保护装置的维护与故障处理

继电保护装置是电力系统运行中不可或缺的基本设备之一,它可以实时监控系统中其他设备的运行状况,并对运行异常问题及时做出处理反应。所以,保障机电保护装置运行的安全性和可靠性对于整个电力系统来说都是非常重要的,本文中笔者就将结合自己的工作经验,谈谈如何对继电保护装置进行维修和故障处理。     

Yj23接咀机水松纸开卷夹持装置的改进

总结原装置的工作繁琐、生产率低的弱点,简要说明新装置的设计思路及设计原理,并总结新装置的特点.     

商用车组装线平衡及案例研究

针对某商用车有限公司组装线自动化程度不高、作业繁杂的现状,应用三项原则对其予以简化,根据组装线平衡理论进行建模,在不改变原组装线布局基础上,采用重要位置排序法初始化作业分配方案,通过作业交换和转移操作,设置合理的参数数值,进行迭代优化.所得结果可大幅提高生产率;另外通过改进组装线布局,生产率可得到进一步提高.     

变电站防误闭锁系统故障原因及处理方法

随着电力系统不断建设扩大,电网安全越来越重要,防误闭锁装置的运用也逐步普及。在运行中防误闭锁系统会出现一些故障,它将严重影响着设备的操作质量、运行人员操作安全。通过对防误闭锁系统在运用中出现的故障原因分析,提出了解决问题的处理方法和加强维护的措施,从而提高防误闭锁装置在运行中的质量,有效避免误操作事故的出现,提高防误闭锁在电力系统中运用的可靠性、稳定性、安全性。     

Electroplating production scheduling by cyclogram unfolding in dynamic hoist scheduling problem

This article presents a scheduling problem that exists in electroplating lines. An electroplating line is an automated manufacturing system which covers machine parts with a coat of metal. It consists of a set of tanks that chemically process the items and hoists that transport the items between workstations. Scheduling the movements of these hoists is commonly called a hoist scheduling problem. The most common approaches to the problem are cyclic hoist scheduling problem and dynamic hoist scheduling problem (DHSP). This article presents a DHSP solution method. The method divides the problem into real time and non-real time. Special schedules, called cyclograms, allow minimisation of the length of non-real time calculations. A notion of the problem is introduced, an outline of a scheduling system is presented, as well as the heuristic algorithm itself. The results of the described method, referred to as a cyclogram unfolding method, are compared to several cases available in the literature.     

Cyclic scheduling of a single hoist in extended electroplating lines: a comprehensive integer programming solution

This paper studies the single-hoist cyclic scheduling problem in electroplating systems with two extended features. One extension is that the products must visit some processing tanks more than once (multi-function tanks). Another is that more than one identical tank is used at some stages. These extensions are common in practical electroplating lines and can increase the lines' processing capacity. However, they make the hoist scheduling problem more complicated and little research has been done to optimize the hoist moves in such extended practical systems. In this paper, we develop a comprehensive mixed integer linear programming model to find optimal solutions to the single-hoist cyclic scheduling problem for electroplating lines with these extensions. Examples are given to demonstrate the effectiveness of the model in different types of problems.     

Mixed-integer linear programming method for multi-degree and multi-hoist cyclic scheduling with time windows

Multi-degree cyclic hoist scheduling and multi-hoist cyclic scheduling are both capable of improving the throughput in an automatic electroplating line. However, previous research on integrated multi-degree and multi-hoist cyclic scheduling is rather limited. This article develops an optimal mixed-integer linear programming model for the integrated multi-degree and multi-hoist cyclic scheduling with time window constraints. This model permits overlap on hoist coverage ranges, and it proposes new formulations to avoid hoist collisions, by which time window constraints and tank capacity constraints are also formulated. A set of available benchmark instances and newly generated instances are solved using the CPLEX solver to test the performance of the proposed method. Computational results demonstrate that the proposed method outperforms the zone partition heuristic without overlapping, and the throughputs are improved by a significant margin using the proposed method, especially for large-size instances.     

Intelligent scheduling of discrete automated production line via deep reinforcement learning

The reinforcement learning (RL) is being used for scheduling to improve the adaptability and flexibility of an automated production line. However, the existing methods only consider processing time certain and known and ignore production line layouts and transfer unit, such as robots. This paper introduces deep RL to schedule an automated production line, avoiding manually extracted features and overcoming the lack of structured data sets. Firstly, we present a state modelling method in discrete automated production lines, which is suitable for linear, parallel and re-entrant production lines of multiple processing units. Secondly, we propose an intelligent scheduling algorithm based on deep RL for scheduling automated production lines. The algorithm establishes a discrete-event simulation environment for deep RL, solving the confliction of advancing transferring time and the most recent event time. Finally, we apply the intelligent scheduling algorithm into scheduling linear, parallel and re-entrant automated production lines. The experiment shows that our scheduling strategy can achieve competitive performance to the heuristic scheduling methods and maintains stable convergence and robustness under processing time randomness.     

A mixed integer linear programming solution for single hoist multi-degree cyclic scheduling with reentrance

This article considers single hoist multi-degree cyclic scheduling problems with reentrance. Time window constraints are also considered. Firstly, a mixed integer programming model is formulated for multi-degree cyclic hoist scheduling without reentrance, referred to as basic lines in this article. Two valid inequalities corresponding to this problem are also presented. Based on the model for basic lines, an extended mixed integer programming model is proposed for more complicated scheduling problems with reentrance. Phillips and Unger's benchmark instance and randomly generated instances are applied to test the model without reentrance, solved using the commercial software CPLEX. The efficiency of the model is analysed based on computational time. Moreover, an example is given to demonstrate the effectiveness of the model with reentrance.     

Work sequencing in a manufacturing cell with limited labour constraints

This study focuses on the analysis of group scheduling heuristics in a dual-constrained, automated manufacturing cell, where labour utilization is limited to setups, tear-downs and loads/unloads. This scenario is realistic in today's automated manufacturing cells. The results indicate that policies for allocating labour to tasks have very little impact in such an environment. Furthermore, the performance of efficiency oriented, exhaustive, group scheduling heuristics deteriorated while the performance of the more complex, non-exhaustive heuristics improved. Thus, it is recommended that production managers use the simplest labour scheduling policy, and instead focus their efforts to activities such as job scheduling and production planning in such environments.     

Multi-degree cyclic hoist scheduling with time window constraints

This paper deals with the multi-degree cyclic single-hoist scheduling problem with time window constraints, in which multiple identical parts enter and leave the system during each cycle. We propose an analytical mathematical model and a branch-and-bound algorithm so as to find a cyclic sequence of hoist moves that maximises the throughput. The branch-and-bound algorithm implicitly enumerates the sequence of hoist moves and requires the solution of a specific set of linear programming problems (LPPs). Computational results on benchmark instances and randomly generated test instances are presented.     

Cyclic hoist scheduling in large real-life electroplating lines

This paper addresses cyclic scheduling of a single hoist in large real-life electroplating lines, where a part visits some processing tanks more than once and multiple duplicate tanks are used at some production stages having long processing times. We present a formal analysis of the problem and propose an efficient branch-and-bound algorithm. The developed analytical properties allow us to considerably eliminate dominated or infeasible solutions in the branch-and-bound procedure. Computational results on benchmark and real-life instances show that the algorithm is very efficient in scheduling large electroplating lines.     

Sequencing, Scheduling and Tooling Single-Stage Multifunctional Machines in a Small Batch Environment

Single-Stage multifunctional Machining Systems (SSMSs) are an important integral part of automated, flexible manufacturing systems. However, the SSMS frequently becomes the bottleneck of the entire manufacturing system by virtue of protracted internal set-up requirements. A key aspect of achieving full SSMS utilization is the ability to reduce as much as possible these demands at the expense of increasing external set-up. As of today, fixturing devices have not received much attention in the modeling literature. Nevertheless, fixturing devices are in some cases a limited resource which, may affect the shop scheduling decisions and the shop performance and as such can not be omitted. This study presents a {0–1} programming model which takes the fixturing device's limitation in to consideration when determining the weekly sequence of jobs to be produced. The model tries to minimize the non-productive machine time. Based on this model, a heuristic procedure is developed and tested using data of four production weeks obtained from a hi-tech company that produces medical imaging systems.